| Abstract |
My talk will present an investigation into a population of robots that evolves through embodied evolution --- an evolutionary process that is not centrally controlled, but emerges from robot interactions just as natural evolution does.
The robots select their partners randomly, without reference to any assessment of task performance, but the environment is biased to promote task behaviour by awarding additional lifetime to robots that pick up pucks.
The experiments show that the robots do learn to pick up pucks in such a setting. Contrary to what one might expect, increasing the amount of additional lifetime awarded decreases task performance for all settings considered.
Closer analysis shows that this decrease is in part due to the fact that the increased lifespan decreases the number of opportunities to spread a robot's genome, but that increasing the award level also negatively affects selection pressure when there is opportunity for robots to spread their genome.
We conclude that higher rewards overly emphasise one aspect of robot behaviour and in doing so prevent evolution from exploring the behaviour space. |